my_awesome_food_model/test-10-image

README.md

@@ -3,6 +3,8 @@ license: apache-2.0
 base_model: google/vit-base-patch16-224-in21k
 tags:
 - generated_from_trainer
+metrics:
+- accuracy
 model-index:
 - name: my_awesome_food_model
   results: []
@@ -15,13 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 4.5844
-- eval_accuracy: 0.0223
-- eval_runtime: 157.6185
-- eval_samples_per_second: 96.118
-- eval_steps_per_second: 0.755
-- epoch: 1.0
-- step: 118
+- Loss: 4.5151
+- Accuracy: 0.0
 
 ## Model description
 
@@ -41,19 +38,28 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 128
-- eval_batch_size: 128
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 512
+- total_train_batch_size: 64
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 30
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 1    | 4.7400          | 0.0      |
+| No log        | 2.0   | 2    | 4.5670          | 0.0      |
+| No log        | 3.0   | 3    | 4.5151          | 0.0      |
+
 
 ### Framework versions
 
 - Transformers 4.39.3
-- Pytorch 2.1.2
+- Pytorch 2.1.2+cpu
 - Datasets 2.18.0
 - Tokenizers 0.15.2

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:02ebfdda8f585d693f0d6759a61eeeefd9c10b2d4ed8b81be64db4da8d600f09
+oid sha256:09678eb45766da3591c88252b0766c7348813d59b5d78845cb12ec666dbf6a5e
 size 343528508